# 构建用户画像
from collections import OrderedDict
import io
import csv
import json
import sys

from py2neo import Graph
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.metrics.pairwise import cosine_similarity
from py2neo import Graph
import redis
from bulid_distance import city_similarity, read_cities_data, get_ex_cities

sys.stderr = io.TextIOWrapper(sys.stderr.buffer, encoding='utf-8')
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')

citycsv = open('data/job.csv', 'r', encoding="utf-8")
cityreader = csv.reader(citycsv)
jobData = list(cityreader)

# 连接到 Redis 服务器
redis_client = redis.StrictRedis(host='8.140.243.61', port=6210, db=0)




if __name__ == '__main__':
    argument = ''
    # 打印传递的参数
    if len(sys.argv) > 1:
        argument = sys.argv[1]

    # json = job_search(argument)
    print(json)

    # json = get_all_job()
    # print(json)
